Targeting TGF-β1 by employing a vaccine ameliorates fibrosis in a mouse model of chronic colitis
Bibliographic record
Abstract
BACKGROUND: Intestinal fibrosis and stricture formation are major complications of inflammatory bowel disease (IBD), for which there are currently few effective treatments. We sought to investigate whether targeting transforming growth factor-beta1 (TGF-beta1), a key profibrotic mediator, with a peptide-based virus-like particle vaccine would be effective in suppressing intestinal fibrosis by using a mouse model of 2,4,6-trinitrobenzene sulfonic acid (TNBS)-induced chronic colitis. METHODS: The vaccine was prepared by inserting a peptide derived from mouse TGF-beta1 into a carrier hepatitis B core antigen using gene recombination methods. Chronic colitis was induced in BALB/c mice by 8 weekly TNBS administrations. Mice were subcutaneously injected with vaccine, carrier, or phosphate-buffered saline (PBS) in 2 separate studies: either before or after acute inflammatory responses commenced. RESULTS: Sera from vaccinated mice exhibited significantly elevated levels of TGF-beta1-specific immunoglobulin G (IgG), which inhibited TGF-beta1-induced luciferase production in mink lung epithelial cells. In the chronic colitis model, mice receiving vaccine showed improved body weight gain and significantly reduced colonic collagen deposition. Hematoxylin and eosin staining and semiquantitative scoring indicated that vaccination even ameliorated colonic inflammation. Cytokine profile analysis revealed that levels of TGF-beta1, interleukin (IL)-17, and IL-23 in vaccinated mouse colon tissues were decreased, and that percentages of IL-17-expressing CD4(+) lymphocytes in mesenteric lymph node cells were reduced. Furthermore, Smad3 phosphorylation, a key event in TGF-beta signaling, was decreased in colonic tissue in vaccinated mice. CONCLUSIONS: This TGF-beta1 peptide-based vaccine, which suppressed excessive TGF-beta1 bioactivity, may prevent the development of intestinal fibrosis and associated complications, presenting a novel approach in the treatment of IBD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".